import random
import matplotlib.pyplot
import numpy

def matrixCreate(rows,columns):
    return [[0 for x in xrange(columns)] for x in xrange(rows)]

def matrixRandomize(v):
        for row in range(len(v)):
            for column in range(len(v[row])):
                v[row][column] = random.random()
        return v

def initializeNeurons(neuronValues):
    for column in range(len(neuronValues[0])):
        neuronValues[0][column] = random.random()
    return neuronValues

def calculateNeuronPositions(matrix):
    numNeurons = len(matrix[0])
    angle = 0.0
    angleUpdate = 2*numpy.pi/numNeurons
    for i in range(0,numNeurons):
        x = numpy.sin(angle)
        y = numpy.cos(angle)
        angle = angle + angleUpdate
        matrix[0][i] = x
        matrix[1][i] = y
    return matrix

def createSynapses(matrix):
    for row in range(len(matrix)):
        for column in range(len(matrix[row])):
            matrix[row][column] = random.uniform(-1,1)
    return matrix

def plotNeurons(neuronPositions):
    for i in range(len(neuronPositions[0])):
        matplotlib.pyplot.plot(neuronPositions[0][i],neuronPositions[1][i],'ko',markerfacecolor=[1,1,1], markersize=18)
    matplotlib.pyplot.show()
    return

def plotSynapses(neuronPositions):
    for i in range(len(neuronPositions[0])):
        for j in range(len(neuronPositions[0])):
            matplotlib.pyplot.plot([neuronPositions[0][i],neuronPositions[0][j]],[neuronPositions[1][i],neuronPositions[1][j]], color=[0,0,0])
    matplotlib.pyplot.show()
    return

def plotSynapsesWeighted(neuronPositions,synapses):
    for i in range(len(neuronPositions[0])):
        for j in range(len(neuronPositions[0])):
            weight = [0,0,0]
            if synapses[i][j] < 0:
                weight = [.8,.8,.8]
            matplotlib.pyplot.plot([neuronPositions[0][i],neuronPositions[0][j]],[neuronPositions[1][i],neuronPositions[1][j]], color=weight)
    matplotlib.pyplot.show()
    return

def plotSynapsesWeightedMagnitude(neuronPositions,synapses):
    for i in range(len(neuronPositions[0])):
        for j in range(len(neuronPositions[0])):
            w = int(10*abs(synapses[i][j]))+1
            weight = [0,0,0]
            if synapses[i][j] < 0:
                weight = [.8,.8,.8]
            matplotlib.pyplot.plot([neuronPositions[0][i],neuronPositions[0][j]],[neuronPositions[1][i],neuronPositions[1][j]], color=weight, linewidth=w)
    matplotlib.pyplot.show()
    return

def Update(neuronValues,synapses,i):
    if i != 0:
        for j in range(len(neuronValues[0])):
            temp = 0
            for k in range(len(neuronValues[0])):
                temp += synapses[j][k]*neuronValues[i-1][k]
            if temp<0:
                temp=0
            if temp>1:
                temp=1
            neuronValues[i][j] = temp
    return neuronValues

neuronValues = matrixCreate(50, 10)#50 is the number of time steps, and 10 is the number of neurons
neuronValues = initializeNeurons(neuronValues)
neuronPositions = matrixCreate(2,10)
neuronPositions = calculateNeuronPositions(neuronPositions)
#plotNeurons(neuronPositions)
synapses = matrixCreate(10,10)
synapses = createSynapses(synapses)
#plotSynapses(neuronPositions)
#plotSynapsesWeighted(neuronPositions,synapses)
#plotSynapsesWeightedMagnitude(neuronPositions,synapses)
for i in range(50):
    Update (neuronValues,synapses,i)
matplotlib.pyplot.imshow(neuronValues, cmap=matplotlib.pyplot.cm.gray, aspect='auto', interpolation='nearest')
matplotlib.pyplot.show()